[AISWorld] 2ND CFP: HICSS-52 AI, Machine Learning, IoT, & Analytics: Exploring the Impliations for KM & Innovation Management

Rhonda Syler rhonda.syler at gmail.com
Mon Apr 16 19:01:42 -04 2018


*MINI-TRACK: AI, Machine Learning, IoT, and Analytics: Exploring the
Implications for Knowledge Management & Innovation*



The exponential growth of data-intensive technologies such as IoT, IoMT,
augmented reality, machine learning applications, and artificial
intelligence is creating a rich landscape for the collection, organization,
storage, and dissemination of knowledge. The implications of the impact
these technologies have on the knowledge management ecosystem include
process integration issues, data storage and data management challenges,
behavioral issues such as trust in output from these technologies, and even
challenges in the analytics process. Additionally, understanding the
potential impacts of these systems helps inform how to build and use the
infrastructures and processes to achieve improved decision making and
organizational performance.

This mini-track seeks a focus on studies that contribute to the
understanding of the characteristics of these artifacts and the challenges
they present in the context of knowledge management and knowledge creation.
All aspects of the impacts of these artifacts on any facet of knowledge
management - knowledge capture, acquisition, transfer, storage, and flow –
as well as the behavior implications of the development and use of such
systems are within the scope of interest.

We welcome both theoretical and design-science based papers that focus on
AI, machine learning, IoT, IoMT or other related data-intensive
technologies as it relates to KM or knowledge innovation. Paper topics
include, but are not limited to:
·         All aspects of the impacts of AI on knowledge management -
knowledge capture,      acquisition, transfer, storage, and flow – as well
as the behavior implications of the development and use of such systems
·         Studies that focus on the interactions between man and machine,
particularly in terms of knowledge acquisition, transfer, management, and
storage
·         Development frameworks for the use of big data flows
·         Papers that focus on the challenges of data storage from
cognitive computing systems
·         Management and construction of disparate data sources focused on
the Internet of Things
·         Papers that focus on the behavioral aspect of the interactions
between man and machine such as trust and cognitive effort
·         Studies examining the factors that influence the development,
adoption, use and success of cognitive computing systems
·         Empirical studies converting big data to actionable information
and knowledge
·         Case Studies on data scientist success
·         Studies that examine the role of analytics or visualization in
cognitive computing ecosystems
·         Methodologies for determining the frequency and granularity of
data stream snapshots necessary for knowledge creation
·         Papers that make a theoretical contribution to the dynamics of
the interaction between man and machine in the context of cognitive
computing systems


*Papers must be submitted through HICSS-52 submission system. For more
information and submission instructions, visit **http://*
*http://hicss.hawaii.edu/*
<http://amcis2016.aisnet.org/index.php/sessions/call-for-papers>*. For
other questions contact mini-track chairs, Ron Freeze,*
*rfreeze at walton.uark.edu* <rfreeze at walton.uark.edu>*, or Rhonda Syler, *
*rsyler at walton.uark.edu* <rsyler at walton.uark.edu>*, University of Arkansas.*


*IMPORTANT DATES:*
*Paper Submission Deadline*: June 15, 2018, 11:59 p.m. HST

*Notice of Acceptance/Rejection:* August 17, 2018

*Final Manuscripts for Publication Due:* September 22, 2018

*Deadline for at least one author to register:* October 1, 2018

*Mini-track Co-chairs:*

*Ronald D. Freeze (Primary Contact)                      Rhonda A. Syler*

Department of Information Systems                          Department of
Information Systems

University of Arkansas                                             University
of Arkansas

Sam M. Walton College of Business                         Sam M. Walton
College of Business

204 Business Building                                             204
Business Building

1 University of Arkansas                                          1
University of Arkansas

Fayetteville, Arkansas 72701-1201                            Fayetteville,
Arkansas 72701-1201

(479) 575-6961 Direct                                              (479)
575-4743 Direct

(479) 575-4168 Fax                                                 (479)
575-4168 Fax

e-mail: rfreeze at walton.uark.edu                                 e-mail:
rsyler at walton.uark.edu



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